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    Optimizing the Gain and Directivity of a Microstrip Antenna with Metamaterial Structures by Using Artificial Neural Network Approach
    (Springer, 2021) Sağık, Metin; Altıntaş, Olcay; Ünal, Emin; Özdemir, Ersin; Demirci, Mustafa; Çolak, Şule; Karaaslan, Muharrem
    The purpose of this study is to improve the gain and directivity of the microstrip patch antenna by means of metamaterial (MTM) structures. As it is known, antennas have power densities in a certain direction, and the radiation curves of the antennas are shaped by orienting them according to this power density. Based on this feature of the antennas, it is aimed to improve the gain and directivity of microstrip patch antennas with the most suitable structures thanks to metamaterial (MTM) structures. The MTM structures designed are interacted with the antenna. Then, the frequency, gain and directivity of the antenna are trained by the artificial neural network technique to estimate the most appropriate values. As a result, the gain and directivity of the antenna are improved by the interaction of microstrip patch antenna and MTM structures and the results are interpreted on the figures. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.